Sr. Data Engineer

Channel Factory provides intelligent marketing solutions for the next generation of contextual safety, suitability, and performance for brands and agencies. Our platform helps marketers implement, automate, and scale their marketing programs across the world’s largest video library, YouTube and emerging growth channels. We sit at the intersection of marketing and suitability and have a mission of enabling the world’s top brands to consciously connect with the right audience in the right context, maximizing suitability and contextual performance. 

Channel Factory embodies a strong start-up culture that values diversity, collaboration, and results. Our bias towards execution balances critical thinking, analysis, and pragmatic problem solving. We expect a lot from one another and value our thoughtful and intellectually curious company culture. 

Channel Factory is headquartered in the United States and has global offices across 20+ cities/countries. This position will be based in the United States. Remote work status is subject to change at any time.

Channel Factory is in search of an innovative and dedicated Senior Data Engineer to join our growing team that will lead, build, and maintain scalable data infrastructure that powers our analytics and business intelligence initiatives. This is a high-impact role where you will play a pivotal part in evolving our core data infrastructure.

Responsibilities:

• Modernize core ETL processes by refactoring our existing Python / OpenSearch / SQL (PostgreSQL) based ETL systems to land data in our Data Lakehouse (Apache Iceberg)
• Collaborate with product managers and business stakeholders to understand complex business requirements to translate business needs into well-designed and maintainable solutions
• Ensure data quality and reliability by implementing robust data quality checks, monitoring, and alerting to ensure the accuracy and timeliness of all data pipelines
• Create data governance policies and develop data models and schemas optimized for analytical workloads
• Influence the direction for key infrastructure and framework choices for data pipelining and data management
• Manage complex initiatives by setting project priorities, deadlines, and deliverables
• Collaborate effectively with distributed team members across multiple time zones, including offshore development teams
• Build relationships and foster team cohesion across geographical and cultural boundaries
• All other tasks as required.